OpenMachine-ai/transformer-tricks
A collection of tricks and tools to speed up transformer models
This project offers methods to streamline and accelerate large language models, especially those built on the transformer architecture. It takes existing transformer model implementations and applies optimizations, resulting in faster execution and reduced memory usage. This is for machine learning engineers and researchers who are developing, deploying, or fine-tuning transformer-based AI models.
197 stars. Available on PyPI.
Use this if you are working with transformer models and need to improve their speed, reduce their memory footprint, or make them more computationally efficient.
Not ideal if you are looking for a pre-trained model or a high-level API for natural language processing without needing to delve into architectural optimizations.
Stars
197
Forks
12
Language
TeX
License
MIT
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
Dependencies
3
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